Synopsis

This study introduces an image-based
technique for prospective motion correction in multiband fMRI utilizing
multislice-to-volume image registration. Motion detection is based on a single
multiband excitation and readout, which allows a high temporal resolution and does
not depend on the repetition time or the total number of slices. Results show
high accuracy in correcting involuntary as well as intentional head movements
in typical fMRI experiments. Residual motion parameters were observed to be
within the ranges ±0.2mm/±0.2° without and
±0.5mm/±0.5° with intentional head movements. Comparison with volume-to-volume
based prospective motion correction demonstrated an improved performance for
high-frequency components of motion.

Introduction

Head motion is among the most common
reasons for image artifacts and slice misalignments in functional Magnetic
Resonance Imaging (fMRI). Prospective motion correction can reduce the motion
to be corrected by post processing algorithms. Volume-to-volume based
prospective motion correction1 comes with the disadvantages of low
temporal resolution and missing intra-volume correction. Temporal resolution
can be increased with multiband sequences and simultaneous multislice (SMS) image
reconstruction2,3. In earlier work we introduced the use of
multislice-to-volume image registration for navigated prospective motion
correction in spin-echo sequences (MS-PACE)4. In this work, a
self-navigated multiband version of the method is introduced to fMRI that achieves
prospective motion correction using a single, simultaneous multislice
excitation and further increases temporal resolution of the motion correction.

Methods

Figure 1 shows the MS-PACE technique for
a multiband factor of three. First, a single-band reference volume is acquired
to provide auto-calibration data for separating slices in subsequent multiband acquisitions;
this slice separation is performed using the split slice-GRAPPA technique5.
The first volume of multiband scans is then used as reference volume for prospective
motion correction. The next separated slices create the input for the first
multislice-to-volume image registration to the reference volume, based on the Mattes’
Mutual Information metric6 (ITK). The detected motion parameters
are then used in real time to adapt the slice position and orientation of subsequent
scans.

The method was evaluated at 3T (MAGNETOM Skyra,
Siemens Healthcare GmbH) using a well-established fMRI paradigm (fig. 2)
without head restraint. The repeating task consisted of a 22-second pause
followed by an inverting checker board pattern, together with a button-pressing
instruction. The button order was changed between the stimulation phases and
introduced immediately before the task began.

The measurement protocol was performed without any, with
multislice-to-volume (MS-PACE) and with the manufacturer’s volume-to-volume based
prospective motion correction, both with and without intentional head motion. The
protocol parameters of the dedicated T2*-weighted EPI sequence were: TR=1100ms,
TE=30ms, 42 slices, 3mm slice thickness, no slice gap, 64x64 matrix with
192x192mm FOV, 275 volumes, flip angle of 64°, and multiband factor 3.

Results

The average time to separate three
simultaneously excited slices was
40ms; MS-PACE image registration took about 70ms; each slice position was
corrected using the most recent motion update available.

Figures 3 and 4 show residual motion
parameters, detected by SPM127. The motion estimates of measurements
without intentional head movements (fig. 3) show that, without prospective
motion correction, there is a small amount of motion due to the missing head
restraint and the effect of the fMRI tasks performed. Both motion correction
techniques were able to reduce this motion to below ±0.2mm for translations and ±0.2° for rotations.

The motion parameter estimates of
measurements with deliberate head motion (fig. 4) indicate that the MS-PACE
motion correction reduced the residual motion to below ±0.5mm/±0.5° despite the significant motion shown in the curves of the
measurement without prospective motion correction. This type of motion could
not be fully corrected by the volume-to-volume based technique.

Preliminary results of the SPM12 analysis
of the MS-PACE corrected data can be seen in figure 5. The point of highest
activation in the left motor cortex is marked in the images and the corresponding
fitted and adjusted response function is shown graphically.

Discussion

The images from measurements with voluntary
head movements show typical motion effects, often seen when scanning
uncooperative subjects. Volume-to-volume based prospective motion correction is
not able to sufficiently correct for these motion events due to low temporal
resolution, even with a short TR of 1100ms. The MS-PACE technique, however,
offers fast motion-correction updates and can reduce the residual motion significantly.
Results of measurements without intentional head movements indicate that there
is a small increase in residual motion using MS-PACE compared to
volume-to-volume based motion correction.

In this work, a multiband factor
of three was applied. However, the MS-PACE technique could be combined with other
multiband factors with a slight adaption of image registration parameters. An
increased number of simultaneously excited slices would increase the accuracy
of motion detection, but also the computing time for separating the multiband
slices and image registration.

Conclusion

This study has extended the application
of MS-PACE prospective motion correction to multiband fMRI. MS-PACE uses separated
slices from a single multiband readout to perform a multislice-to-volume image
registration to a reference volume. It offers higher temporal resolution compared to volume-to-volume based methods and is able to correct intra-volume
motion. The method can be used with a range of multiband factors and shows a
substantial reduction of residual motion parameters in the presence of significant subject
motion.

Acknowledgements

The Authors are grateful to Dr
Robert Frost and the Welcome Centre For Integrative Neuroimaging at Oxford
University for providing source code for their slice-GRAPPA implementation.
Thanks are also due to Klaus Eickel for his
contributions to the SMS methods used in this study.

All funding
for this study was provided by the internal Attract funding
program of the German Fraunhofer-Gesellschaft.

Figures

Figure 1: Overview of
the proposed prospective motion correction technique (MS-PACE) using
multislice-to-volume image registration in multiband fMRI for the example of a multiband
factor of three. The technique includes the acquisition of a single-band
reference volume to provide auto-calibration data, the acquisition of a multiband
reference volume for the prospective motion correction, the multiband imaging
scans, which are used as input for a multislice-to-volume image registration,
and the real-time feedback to the sequence to adapt the imaging system
according to the detected motion.

Figure 2: Time course
of the fMRI stimulation protocol which was used in all measurements. A visual stimulation
was combined with a button-pressing task and alternated with a 22-second pause.
The button-pressing sequences were varied and communicated to the volunteer
prior to each stimulation phase.

Figure 3: Motion-parameter estimates
determined by SPM12 for measurements acquired with volume-to-volume based
prospective motion correction (red), MS-PACE prospective motion correction
(black) and without prospective motion correction (green). The volunteer
performed a standard fMRI task during the measurements and did not perform
intentional head movements.

Figure 4: Motion-parameter estimates
determined by SPM12 for measurements acquired while performing an fMRI task and
intentional head movements. The curves show the residual motion after
volume-to-volume based prospective motion correction (red), after MS-PACE
prospective motion correction (black) and without prospective motion correction
(green).

Figure 5: Preliminary results of SPM12
fMRI analysis using the MS-PACE corrected data from measurements with
intentional head movements. The fitted and adjusted response function (bottom) corresponds
to the voxel with the highest activation in the left motor cortex indicated in
the images (top).